Code Acts in Education: Nudging Assets
The acquisition of the global education platform Blackboard by Anthology has brought the mundane Learning Management System back to attention. While full details of the deal remain to be seen, and it won’t be closed until the end of the year, it surfaces two important and interlocking issues. One is the increasing centrality of huge data integrations to the plans of education technology vendors, and the second is the seeming attractiveness of the data-driven approach to edtech financiers.
Primarily, the acquisition of Blackboard by Anthology centres on business interests, according to edtech consultant Phil Hill, who notes that Blackboard’s owners have been seeking to sell the company for three years. The purpose of the deal, Hill argues, ‘is a revenue growth opportunity driven by cross-selling, international growth, and the opportunities to combine products and create new value, particularly at the data level.’ This approach, Hill further suggests, makes sense on the ‘supply side’ for vendors and investors who see value in combining data and integrating systems, if less so on the ‘demand side’ of universities and schools, whose primary concerns are with usability.
There are two things going on here worth questioning a little further. First, what exactly are Blackboard/Anthology hoping to achieve by combining data, and second, why is this attractive to investors? Based on some recent company blog posts from Blackboard, the answer to the first question appears to be about the capacity for ‘nudging’ students towards better outcomes through ‘personalized experiences’ based on data analytics, and the second question might be addressed by understanding those data as ‘assets’ with expected future earnings power for their owners. This post is an initial attempt to explore those issues and their interrelationship.
One of the key features of the Blackboard/Anthology announcement was that it would enable much greater integration of the existing software systems of the two companies, including Learning Management System, community engagement, student success, student information system and enterprise resource planning. ‘Combining the two companies will create the most comprehensive and modern EdTech ecosystem at a global scale for education’, the CEO, president and chair of Blackboard, Bill Ballhause wrote in a company blog. ‘It will enable us to break down data silos, and surface deeper insights about the learner so we can deliver unmatched personalized experiences across the full learner lifecycle and drive better outcomes’.
The idea of breaking down ‘data silos’ and integrating data systems is part of a longer Blackboard strategy on making the most of cloud computing for cross-platform interoperability. Blackboard migrated most of its services to Amazon Web Services starting in 2015, with reportedly significant effects on how it could make use of the data collected by its LMS. ‘Our new analytics offering, Blackboard Data, is a good example where we are leveraging AWS technologies to build a platform that provides data-driven insight across all our solutions’, Blackboard reported in 2017. These insights will now be generated across the entire Blackboard/Anthology portfolio, raising data privacy and protection implications that Blackboard was quick to address just a day after the announced acquisition.
Beyond data privacy issues, though, the stated purpose of integrating data is to enact ‘Blackboard’s vision of personalizing experiences’. Writing earlier in the summer, Blackboard’s CEO Bill Ballhaus set out the company’s longer-term vision for personalizing learning experiences. Drawing on examples of online shopping, healthcare and entertainment, Ballhaus argued that a ‘critical mass of data powers proactive nudges’ based on highly granular personal data profiles. Education, however, had not yet ‘kept pace with the shift to customized experiences that other industries achieved’. This, he said, had now changed with the disruptions of the previous year.
‘The massive shift to online learning driven by the COVID-19 global pandemic enabled continuity of education in the near term, while opening the door for education to move forward on a journey toward more personalized experiences’, Ballhaus argued. ‘We’ve had our sights set on the future for the past few years and have the ability to securely harness data, with robust privacy protections, from across our ecosystem of EdTech solutions with the specific intent of enabling personalized experiences to drive improved outcomes’.
The discourse of ‘nudges’ as the central technique of personalized learning runs throughout this vision. ‘Students need nudges’ to reach better outcomes, Ballhaus continued, with ‘the 25 billion weekly interactions in our learning management and virtual classroom systems’ enabling Blackboard to operationalize such a nudge-based approach to personalized learning.
By emphasizing student nudges fuelled by masses of data as the basis of personalized learning, Blackboard has tapped into the logics of the psychological field of behavioural economics and its political uptake in the form of behavioural governance. Mark Whitehead and coauthors describe how behavioural governance has proliferated across public policy in many countries in recent years—especially the UK and US—through the application of nudge strategies. This has been amplified by digital ‘hypernudge’ techniques based on personal data profiles, which, as Karen Yeung argues, ‘are extremely powerful and potent due to their networked, continuously updated, dynamic and pervasive nature’.
So, the business plan behind the Blackboard/Anthology merger appears to be to enact a form of behavioural governance in digital education, operationalizing personalized hypernudges within the architectures of vast edtech ecosystems. While such a form of ‘machine behaviourism’ has existed in imaginary form for some years, it may now materialize in the seemingly mundane machinery of the learning management systems used by institutions across the globe. And that potential capacity for nudging also appears to be the source of expected future value for financial backers.
While the Blackboard/Anthology deal has been presented by the two companies as a merger, and interpreted by most as an acquisition of the former by the latter, in reality this is a deal between their financial backers and owners. Anthology is majority owned by Veritas Capital (a private equity firm investing in products and services to government and commercial customers), with Leeds Equity Partners (a private equity firm focused on investments in the Knowledge Industries) as a minority owner, while Blackboard is owned by Providence Equity Partners (a global private equity investment firm focused on media, communications, education, software and services investments). Veritas is providing new funding and retaining majority shareholder status, with both Leeds and Providence as minority shareholders following the acquisition.
The exact value of the deal remains unknown—Phil Hill has suggested it may be in the region of $3bn—but clearly these three private equity firms see prospects for value creation in the future. To interpret this, we need to understand some of the logic of investment. Recent economic sociology work can help here, particularly the concepts of capitalization and assetization.
As Fabian Muniesa and colleagues phrase it, capitalization refers to the processes and practices involved in ‘valuing something’ in terms of ‘the expected future monetary return from investing in it’. Capitalization, they continue, ‘characterizes the reasoning of the banker, the financier and the entrepreneur’, and calculating future expected returns is central to any form of investment. Capitalization then also depends on seeing something as an asset with future value, or making it into one. Kean Birch and Muniesa define an asset as any resource controlled by its owner as a source of expected future benefits, and ‘assetization’ thus as the processes involved in making that resource into a future revenue stream. Transforming something into an asset is therefore central to capitalization.
Capitalization and assetization may be useful concepts for exploring the Blackboard/Anthology deal. Clearly, Veritas, Leeds and Providence as owners and shareholders are seeking future value from their assets. Their entire business is capitalizing on the assets they hold investments in, in expectation of return on investment. In part, the platforms that Blackboard and Anthology will combine are the assets. It is expected that more customers will purchase from them through cross-selling compatible products (e.g. by integrating Blackboard LMS with Anthology student information systems and making them interoperable for ease of use).
But given the prominence in the deal announcement and other posts of ‘breaking down data silos’ and ‘the possibilities of delivering personalized experiences fueled by data through our combination’, it seems likely that there is a process of assetizing the data themselves going on here. If the platforms and services themselves have future value, that is dependent upon the 25 billion weekly interactions of users as a new source of value creation. How are data made valuable?
In a recent study, Birch and coauthors highlight how ‘Big Tech’ companies transform personal digital data into assets with future earnings power both for the companies and their investors. They transform personal data into assets to generate future revenue streams. And Birch and colleagues argue that this assetization of user data occurs through the ‘transformation of personal data into user metrics that are measurable and legible to Big Tech and other political-economic actors (e.g., investors)’. In similar ways, then, the new Big EdTech company emerging from the combination of Blackboard and Anthology aims to transform student data into measurable and legible forms for their investors. 25 billion weekly interactions leave traces which can be made valuable.
As Janja Komljenovic has recently argued, ‘the digital traces that students and staff leave behind when interacting with digital platforms’ can be ‘made valuable by processing data into intelligence for either improving an existing product or service, or creating a new one, selling data-based products (such as learning analytics or other data intelligence on students), various automated matching services, automated tailored advertising, exposure to the audience, and so on’. The value comes not from the data themselves, but ‘from their predictive power and inducing behaviour in others’. In other words, as Komljenovic elaborates, ‘what becomes valuable in digital education is power over the direction of student and staff teaching, learning and work patterns. It is first about the power over calculating predictions and thus performing future, and second, about tailoring experience and nudging behaviour’.
In this particular sense, then, we can see how the objective of ‘nudging’ students through data-fuelled personalized experience may be a core part of the assetization process involved in the merger of Blackboard and Anthology. The platforms and services themselves as marketable products for institutions to pay for, or the weekly 25 billion data points of interaction with them, are not the only sources of expected value. Instead, the predictive capacity to shape education by personalizing experience and nudging student behaviours appears to be the key to unlocking future revenue streams.
Assetizing the nudge and nudging the asset in Big EdTech
The Blackboard/Anthology deal seems to foreground two complementary trends in the edtech sector. The first is that the ‘nudge’ has become the source of expected future value to asset owners. Personalized learning via digital nudges is clearly a core part of the expected value that Blackboard will return its new private equity owners and shareholders. This is assetizing the nudge.
The second is that student data have become the focus of the nudge, with digital nudges expected to increase student outcomes. In this sense, the masses of student data held by Blackboard/Anthology are being transformed into assets too. And if we understand those data to produce ‘data subjects’ or informational identities of a student, then we might conceivably think of students themselves as assets with value that can be increased through predictive nudging. This is nudging the asset, although it’s too early to see quite how this will work out in practice at the new company or in the institutions that use its services,
Maybe later details on the deal will help us clarify the precise ways assetization and nudging complement one another in an emerging environment of Big EdTech deals and integrations. It is important for critical edtech research to get up-close to these developments at the intersections of nudging and assetization, as practical techniques of behavioural governance and capitalization, even in the most mundane places like the LMS.
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